Tag: Mine

SubPatCNV – Mine CNV Subspace Patterns

SubPatCNV

:: DESCRIPTION

SubPatCNV (Subspace Pattern-ming of Copy Number Variations) is a tool for mining CNV subspace patterns, which is able to identify all aberrant CNV regions specific to arbitrary patient subsets larger than a support threshold. SubPatCNV is an approximate association pattern mining algorithm under a spatial constraint on the positional CNV probe features. In the experiments on a large-scale bladder cancer dataset, SubPatCNV discovered many large aberrant CNV events in patient subgroups and also reported CNV regions highly specific to clinical variables such as tumor grade or stage and enriched with more known oncogenes compared with other existing CNV discovery methods.

::DEVELOPER

Kuang Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / WIndows / MacOsX
  • Matlab

:: DOWNLOAD

  SubPatCNV

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2015 Jan 16;16(1):16. [Epub ahead of print]
SubPatCNV: approximate subspace pattern mining for mapping copy-number variations.
Johnson N, Zhang H, Fang G, Kumar V, Kuang R.

MARQ – Mine GEO for Experiments with Similar or opposite Gene Expression Signatures

MARQ

:: DESCRIPTION

MARQ (Microarray Rank Query) is an online microarray retrieval tool based on rank statistics. Datasets in MARQ, most of them retrieved from GEO, are processed into signatures, which are lists of genes ranked by their level of differential expression. Each dataset defines one of more of these signatures based on the possible comparisons of its constituent samples.

::DEVELOPER

MARQ team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Web Browser

:: DOWNLOAD

 No

:: MORE INFORMATION

Citation

Vazquez, M., Nogales-Cadenas, R., Arroyo, J., Botías, P., García, R., Carazo, J. M., Tirado, F., Pascual-Montano, A. Carmona-Saez, P. 2010,
`MARQ: an online tool to mine GEO for experiments with similar or opposite gene expression signatures.’ ,
Nucleic Acids Res. 2010 Jul;38(Web Server issue):W228-32.

TransposonPSI 20100822 – PSI-Blast to Mine (Retro-)Transposon ORF Homologies

TransposonPSI 20100822

:: DESCRIPTION

TransposonPSI is an analysis tool to identify protein or nucleic acid sequence homology to proteins encoded by diverse families of transposable elements. PSI-Blast is used with a collection of (retro-)transposon ORF homology profiles to identify statistically significant alignments. This method can be used to identify potential transposon ORFs within a protein set, or to identify regions of transposon homology within a larger genome sequence. This is particularly useful to identify degenerate transposon homologies within genome sequences that escape identification and masking by using RepeatMasker and an associated nucleotide library of repetitive elements. TransposonPSI has been routinely used to assist in the discovery of mobile elements across eukaryotes including protozoa, plants, fungi, and animals.

::DEVELOPER

Brian Haas @ Broad Institute

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 TransposonPSI

:: MORE INFORMATION

tYNA – Tool for Managing, Comparing and Mining Multiple Networks

tYNA

:: DESCRIPTION

tYNA (TopNet-like Yale Network Analyzer), a Web system for managing, comparing and mining multiple networks, both directed and undirected. tYNA efficiently implements methods that have proven useful in network analysis, including identifying defective cliques, finding small network motifs (such as feed-forward loops), calculating global statistics (such as the clustering coefficient and eccentricity), and identifying hubs and bottlenecks etc.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 tYNA

:: MORE INFORMATION

Citation:

The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks.
Yip KY, Yu H, Kim PM, Schultz M, Gerstein M.
Bioinformatics. 2006 Dec 1;22(23):2968-70.

CODENSE 1.0 – Mine Coherent Dense Subgraphs from Multiple Biological Networks

CODENSE 1.0

:: DESCRIPTION

CODENSE ( Mining Coherent Dense Subgraphs) is a software package to mine coherent dense subgraphs from multiple biological networks. CODENSE is short for Mining Coherent Dense Subgraphs. By simplifying the problem of identifying coherent dense subgraphs across n graphs into a problem of identifying dense subgraphs in two special graphs: the summary graph and the second-order graph, CODENSE can efficiently mine frequent coherent dense subgraphs across large numbers of massive graphs

::DEVELOPER

the Zhou Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 CODENSE

:: MORE INFORMATION

Citation:

Haiyan Hu, Xifeng Yan, Yu Huang, Jiawei Han and Xianghong Jasmine Zhou
Mining coherent dense subgraphs across massive biological networks for functional discovery
Bioinformatics Volume 21, Issue suppl 1Pp. i213-i221

imCellPhen Alpha – Interactive Mining of Cellular Phenotypes

imCellPhen Alpha

:: DESCRIPTION

imCellPhen (Interactive mining of cellular phenotypes) is an innovative computing paradigm that uses intelligent human-computer interfaces to facilitate the application of the HCS technology in biomedical research. It’s a a new computing paradigm that combines unsupervised pattern mining techniques, P-VDE interfaces, and CBIR-RF techniques to boost the exploitation capacity of the HCS technology and facilitate its application to biomedical research.

::DEVELOPER

Pengyu Hong

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 imCellPhen

:: MORE INFORMATION

Citation

Hong, P. (2006).
Interactive Analysis of High-Content Cellular Images via Relevant Feedback.
2006 Workshop on Multiscale Biological Imaging, Data Mining and Informatics, Santa Barbara, CA, USA.

BioMyn – Mining Gene and Protein Knowledge

BioMyn

:: DESCRIPTION

BioMyn is a comprehensive online resource that integrates information related to human genes and proteins from over a dozen external databases. It includes Gene Ontology annotations of human genes and proteins, sequence family classifications, protein domain architectures, metabolic and signaling pathways, protein interactions and protein complexes, and disease associations.

::DEVELOPER

Max-Planck-Institut Informatik

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 BioMyn

:: MORE INFORMATION